Improved Load Plan Design Through Integer Programming Based Local Search

We present advances both in modeling and algorithm design for a service network design problem faced by less-than-truckload (LTL) freight transportation carriers. The developed models more accurately capture key operations of today’s carriers: decisions for loaded and empty trailer movements are considered simultaneously, and a time discretization is used that can appropriately model the timing of freight consolidation opportunities. In addition to providing decision support for traditional service network plans used by LTL carriers, the models also enable the development of plans that allow more flexibility, such as allowing certain freight routes to vary by weekday. Given the additional detail within the proposed models, very large problem instances result when they are applied to large-scale LTL networks. We therefore propose a local search solution heuristic that searches a large neighborhood each iteration using an integer program. Computational experiments using data from a large U.S. carrier demonstrate that the proposed modeling and solution approach has the potential to generate significant cost savings.